Load Libraries

Note: the ggplot package is contained within the tidyverse library.

Graphics Intro

Make your first figure

  1. Data set
head(diamonds)
carat cut color clarity depth table price x y z
0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43
0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31
0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31
0.29 Premium I VS2 62.4 58 334 4.20 4.23 2.63
0.31 Good J SI2 63.3 58 335 4.34 4.35 2.75
0.24 Very Good J VVS2 62.8 57 336 3.94 3.96 2.48

  1. Begin with the data

  2. Specify the aesthetic mappings

  3. Choose a geom

  4. Add an aesthetic

  5. Add another layer

  6. Mapping aesthetics vs setting aesthetics

  7. Coordinate transformations can be specified

  8. Specify facet variables

Basics

Tidy Your Data

To tidy the preg table use pivot_longer() to create a long table.

## # A tibble: 2 × 3
##   pregnant  male female
##   <chr>    <dbl>  <dbl>
## 1 yes         NA     20
## 2 no          10     12

Solution

## # A tibble: 4 × 3
##   pregnant sex    count
##   <chr>    <chr>  <dbl>
## 1 yes      male      NA
## 2 yes      female    20
## 3 no       male      10
## 4 no       female    12

Layers

Change the code below to have the points on top of the boxplots.

Solution

Perception

Diamonds

In the diamonds data, clarity and cut are ordinal, while price and carat are continuous.

Create a graphic that gives an overview of these four variables while respecting their types.

One possible plot, there will be many!

Movies

The movies data set contains information from IMDB.com including ratings, genre, length in minutes, and year of release. Explore the differences in length, rating, etc. in movie genres over time. Hint: use faceting!

A few different plots, there will be many!

##        X             title                year          length      
##  Min.   :     7   Length:65134       Min.   :1893   Min.   :  1.00  
##  1st Qu.:144108   Class :character   1st Qu.:1954   1st Qu.: 24.00  
##  Median :195320   Mode  :character   Median :1983   Median : 89.00  
##  Mean   :208093                      Mean   :1975   Mean   : 73.36  
##  3rd Qu.:258227                      3rd Qu.:1998   3rd Qu.:100.00  
##  Max.   :411511                      Max.   :2005   Max.   :873.00  
##                                                                     
##      budget              rating           votes            mpaa          
##  Min.   :        0   Min.   : 1.000   Min.   :     5   Length:65134      
##  1st Qu.:   320000   1st Qu.: 5.300   1st Qu.:    12   Class :character  
##  Median :  4000000   Median : 6.300   Median :    32   Mode  :character  
##  Mean   : 15489887   Mean   : 6.138   Mean   :   768                     
##  3rd Qu.: 20000000   3rd Qu.: 7.100   3rd Qu.:   131                     
##  Max.   :200000000   Max.   :10.000   Max.   :157608                     
##  NA's   :58713                                                           
##     genre          
##  Length:65134      
##  Class :character  
##  Mode  :character  
##                    
##                    
##                    
##

Polishing Plots

Palmer Penguins

    install.packages("palmerpenguins")
    data(penguins, package = "palmerpenguins")
    head(penguins)
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex year
Adelie Torgersen 39.1 18.7 181 3750 male 2007
Adelie Torgersen 39.5 17.4 186 3800 female 2007
Adelie Torgersen 40.3 18.0 195 3250 female 2007
Adelie Torgersen NA NA NA NA NA 2007
Adelie Torgersen 36.7 19.3 193 3450 female 2007
Adelie Torgersen 39.3 20.6 190 3650 male 2007

Meet the Palmer penguins & Bill Dimensions by Allison Horst

  1. Create a scatterplot of bill length versus bill width from the penguins data, colored by species

  1. Use the black and white theme

  2. Clean up axis labels and include an informative title.

  1. Capitalize legend title and change the color palette from default.

  2. Move the legend to the bottom and set aspect ratio to 1.

  3. Save your plot to a pdf file and open it in a pdf viewer.

Make sure you know where this is saving to; remember R projects and working directories!

  1. Save a png of the same scatterplot.

  2. Embed the png into MS word or another editor.